Reduced imu power consumption in a wearable device

ABSTRACT

Systems and methods for detecting touch events with an accelerometer are disclosed. In one aspect, a method includes measuring first accelerometer data at a first rate, detecting a first touch event based on the first accelerometer data, in response to detecting the first touch event, measuring second accelerometer data at a second rate, determining whether a second touch event is detected based on the second accelerometer data, measuring third accelerometer data at the first rate in response to an absence of the second touch event being detecting in the second accelerometer data over a predetermined threshold period of time.

CLAIM OF PRIORITY

This application is a continuation of U.S. patent application Ser. No. 17/239,028, filed on Apr. 23, 2021, which is a continuation of U.S. patent application Ser. No. 16/738,497, filed on Jan. 9, 2020, which is a continuation of U.S. patent application Ser. No. 15/798,012, filed on Oct. 30, 2017, each of which are hereby incorporated by reference herein in their entireties.

BACKGROUND

Wearable devices have several design constraints. One of these constraints is weight. Another is size. To reduce size and weight, a wearable device may make use of a relatively small battery. As a result, power consumption of the wearable device can be an important factor in user satisfaction. Therefore, reducing power consumption in wearable devices continues to be an important design consideration.

BRIEF DESCRIPTION OF THE DRAWINGS

Various ones of the appended drawings merely illustrate example embodiments of the present disclosure and should not be considered as limiting its scope.

FIG. 1 is a front perspective view of one embodiment of a camera device.

FIG. 2 is a block diagram illustrating a networked system including details of a camera device, according to some example embodiments.

FIGS. 3 and 4 illustrate wearable devices including transmission components according to certain example embodiments.

FIG. 5 is a state transition diagram that may be implemented in at least some of the disclosed embodiments.

FIG. 6 is a block diagram of an example IMU 215, according to some example embodiments.

FIG. 7 a data flow diagram of one exemplary method of training a model to detect tap inputs based on acceleration data, according to some example embodiments.

FIG. 8 is a flowchart of a method for managing a sampling rate of an inertial measurement unit, according to some example embodiments.

FIG. 9 is a block diagram illustrating an example of a software architecture that may be installed on a machine, according to some example embodiments.

FIG. 10 illustrates a diagrammatic representation of a machine in the form of a computer system within which a set of instructions may be executed for causing the machine to perform any one or more of the methodologies discussed herein.

DETAILED DESCRIPTION

The description that follows includes systems, methods, techniques, instruction sequences, and computing machine program products that embody illustrative embodiments of the disclosure. In the following description, for the purposes of explanation, numerous specific details are set forth in order to provide an understanding of various embodiments of the inventive subject matter. It will be evident, however, to those skilled in the art, that embodiments of the inventive subject matter may be practiced without these specific details. In general, well-known instruction instances, protocols, structures, and techniques are not necessarily shown in detail.

Disclosed are methods, systems, and devices for reducing power consumption in a wearable device. The wearable devices disclosed include an inertial measurement unit (IMU). The IMU may be used to detect motion in the wearable device. The motion detected by the IMU may be used for example, to determine whether to maintain the device in an active state or allow the device to enter a low power state.

In some aspects, the IMU may be controlled through at least three different states. In a first state, the IMU is placed in a low power state. The low power state maintains an IMU sampling rate at a first rate. This rate may be relatively low to reduce power consumption of the IMU. In this state, the IMU may be unable to determine direction of any motion, but instead only detect that the motion is present. A second IMU state may set a sampling rate of the IMU at a second rate. The second rate is higher than the first rate. With this higher second sampling rate, the IMU is able to detect directional information relating to motion. However, the second sampling rate may not support detection of a “double tap” input. For example, the speed of the “double tap” may be too fast for both taps to be accurately detected with the second sampling rate.

Upon detection of a first tap while in the second state, the IMU may be moved to a third state. The third state provides a third sampling rate, higher than the second sampling rate. The third state also enables an acceleration measurement queuing capability that stores acceleration measurements over a period of time.

During a time period after the first tap is detected, the IMU may be maintained in this third state. If no further motion is detected during the time period, the IMU may be transitioned back to the second state. With this transition, the IMU sampling rate returns to the second rate, and the acceleration queuing capability may also be disabled to save further power.

If no motion is detected for a second threshold period of time, the IMU may be transitioned back from the second state to the first state. The sampling rate of the IMU may also be reduced from the second rate to the lower first rate as a result of this transition. By modulating the sampling rate of the IMU based on motion detected, overall power consumption of the IMU may be reduced, while still providing detection of motion and tap events, including both single tap and double tap events.

FIG. 1 shows aspects of certain embodiments illustrated by a front perspective view of glasses 31. The glasses 31 can include a frame 32 made from any suitable material such as plastic or metal, including any suitable shape memory alloy. The frame 32 can have a front piece 33 that can include a first or left lens, display or optical element holder 36 and a second or right lens, display or optical element holder 37 connected by a bridge 38. The front piece 33 additionally includes a left end portion 41 and a right end portion 42. A first or left optical element 43 and a second or right optical element 44 can be provided within respective left and right optical element holders 36, 37. Each of the optical elements 43, 44 can be a lens, a display, a display assembly or a combination of the foregoing. Any of the display assemblies disclosed herein can be provided in the glasses 31.

Frame 32 additionally includes a left arm or temple piece 46 and a second arm or temple piece 47 coupled to the respective left and right end portions 41, 42 of the front piece 33 by any suitable means such as a hinge (not shown), so as to be coupled to the front piece 33, or rigidly or fixably secured to the front piece so as to be integral with the front piece 33. Each of the temple pieces 46 and 47 can include a first portion 51 that is coupled to the respective end portion 41 or 42 of the front piece 33 and any suitable second portion 52 for coupling to the ear of the user. In one embodiment the front piece 33 can be formed from a single piece of material, so as to have a unitary or integral construction. In one embodiment, such as illustrated in FIG. 1, the entire frame 32 can be formed from a single piece of material so as to have a unitary or integral construction.

Glasses 31 can include a computing device, such as computer 61, which can be of any suitable type so as to be carried by the frame 32 and, in one embodiment of a suitable size and shape, so as to be at least partially disposed in one of the temple pieces 46 and 47. In one embodiment, as illustrated in FIG. 1, the computer 61 is sized and shaped similar to the size and shape of one of the temple pieces 46, 47 and is thus disposed almost entirely if not entirely within the structure and confines of such temple pieces 46 and 47. In one embodiment, the computer 61 can be disposed in both of the temple pieces 46, 47. The computer 61 can include one or more processors with memory, wireless communication circuitry, and a power source. As described above, the computer 61 comprises low-power circuitry, high-speed circuitry, and a display processor. Various other embodiments may include these elements in different configurations or integrated together in different ways. Additional details of aspects of computer 61 may be implemented as illustrated by device 210 discussed below.

The computer 61 additionally includes a battery 62 or other suitable portable power supply. In one embodiment, the battery 62 is disposed in one of the temple pieces 46 or 47. In the glasses 31 shown in FIG. 1 the battery 62 is shown as being disposed in left temple piece 46 and electrically coupled using connection 74 to the remainder of the computer 61 disposed in the right temple piece 47. The one or more input and output devices can include a connector or port (not shown) suitable for charging a battery 62 accessible from the outside of frame 32, a wireless receiver, transmitter or transceiver (not shown) or a combination of such devices. In various embodiments, the computer 61 and the battery 62 may consume power as part of glasses operations for capturing images, transmitting data, or performing other computing processes. Such power consumption may result in heat that may impact the device as well as a user wearing the device. Embodiments described herein may function to manage temperature in wearable devices such as glasses 31.

Glasses 31 include cameras 69. Although two cameras are depicted, other embodiments contemplate the use of a single or additional (i.e., more than two) cameras. In various embodiments, glasses 31 may include any number of input sensors or peripheral devices in addition to cameras 69. Front piece 33 is provided with an outward facing, forward-facing or front or outer surface 66 that faces forward or away from the user when the glasses 31 are mounted on the face of the user, and an opposite inward-facing, rearward-facing or rear or inner surface 67 that faces the face of the user when the glasses 31 are mounted on the face of the user. Such sensors can include inwardly-facing video sensors or digital imaging modules such as cameras that can be mounted on or provided within the inner surface 67 of the front piece 33 or elsewhere on the frame 32 so as to be facing the user, and outwardly-facing video sensors or digital imaging modules such as cameras 69 that can be mounted on or provided with the outer surface 66 of the front piece 33 or elsewhere on the frame 32 so as to be facing away from the user. Such sensors, peripheral devices or peripherals can additionally include biometric sensors, location sensors, or any other such sensors.

Embodiments of this disclosure may provide for reduced power consumption of the computer 61. For example, in some aspects, the computer 61 may include an accelerometer or inertial measurement unit that is configured to record accelerations in one or more axis. These accelerations may be used, in some aspects, to detect touch events that may occur on a portion of the glasses 31, such as the frame 32. The accelerometer or inertial measurement unit may consume power. Given a finite life of the battery 62, it may be desirable to operate the accelerometer in such a manner as to more efficiency consume power while meeting the needs of one or more applications running on the glasses 31 that utilize the accelerometer measurements. Embodiments of this disclosure provide for that reduced power consumption, in some aspects, by specifically tailoring a polling or measurement rate of the accelerometer to the needs of the application(s) at a particular point in time, as further discussed below.

FIG. 2 is a block diagram illustrating a networked system 200 including details of a device 210, according to some example embodiments. In certain embodiments, device 210 may be implemented in glasses 31 of FIG. 1 described above. For example, device 210 may be equivalent, in some aspects, to the computer 61.

System 200 includes device 210, client device 290, and server system 298. Client device 290 may be a smartphone, tablet, phablet, laptop computer, access point, or any other such device capable of connecting with device 210 using both a low-power wireless connection 225 and a high-speed wireless connection 237. Client device 290 is connected to server system 298 and network 295. The network 295 may include any combination of wired and wireless connections. Server system 298 may be one or more computing devices as part of a service or network computing system. Client device 290 and any elements of server system 298 and network 295 may be implemented using details of software architecture 902 or machine 1000 described in FIGS. 9 and 10.

System 200 may optionally include additional peripheral device elements 219 and/or a display 211 integrated with device 210. Such peripheral device elements 219 may include biometric sensors, additional sensors, or display elements integrated with device 210. Examples of peripheral device elements 219 are discussed further with respect to FIGS. 9 and 10. For example, peripheral device elements 219 may include any I/O components 1050 including output components, 1052 motion components 1058, or any other such elements described herein. Example embodiments of a display 211 are discussed in FIGS. 3 and 4.

Device 210 includes inertial measurement unit (IMU) 215, camera 214, video processor 212, interface 216, low-power circuitry 220, and high-speed circuitry 230. Camera 214 includes digital camera elements such as a charge coupled device, a lens, or any other light capturing elements that may be used to capture data as part of camera 214. In some aspects, the camera 214 may be the camera 69, discussed above with respect to FIG. 1. While the IMU 215 is shown in FIG. 2 as being included within the device 210, in some aspects, the IMU 215 may be a separate device, and be operably connected, for example, via a communications bus or other interconnect technology, the device 210.

Interface 216 refers to any source of a user command that is provided to device 210. In one implementation, interface 216 is a physical button on a camera that, when depressed, sends a user input signal from interface 216 to low power processor 222. A depression of such a camera button followed by an immediate release may be processed by low power processor 222 as a request to capture a single image. A depression of such a camera button for a first period of time may be processed by low-power processor 222 as a request to capture video data while the button is depressed, and to cease video capture when the button is released, with the video captured while the button was depressed stored as a single video file. In certain embodiments, the low-power processor 222 may have a threshold time period between the press of a button and a release, such as 500 milliseconds or one second, below which the button press and release is processed as an image request, and above which the button press and release is interpreted as a video request. The low power processor 222 may make this determination while the video processor 212 is booting. In other embodiments, the interface 216 may be any mechanical switch or physical interface capable of accepting user inputs associated with a request for data from the camera 214. In other embodiments, the interface 216 may have a software component, or may be associated with a command received wirelessly from another source.

Video processor 212 includes circuitry to receive signals from the camera 214 and process those signals from the camera 214 into a format suitable for storage in the memory 234. Video processor 212 is structured within device 210 such that it may be powered on and booted under the control of low-power circuitry 220. Video processor 212 may additionally be powered down by low-power circuitry 220. Depending on various power design elements associated with video processor 212, video processor 212 may still consume a small amount of power even when it is in an off state. This power will, however, be negligible compared to the power used by video processor 212 when it is in an on state, and will also have a negligible impact on battery life. As described herein, device elements in an “off” state are still configured within a device such that low-power processor 222 is able to power on and power down the devices. A device that is referred to as “off” or “powered down” during operation of device 210 does not necessarily consume zero power due to leakage or other aspects of a system design.

In one example embodiment, video processor 212 comprises a microprocessor integrated circuit (IC) customized for processing sensor data from camera 214, along with volatile memory used by the microprocessor to operate. In order to reduce the amount of time that video processor 212 takes when powering on to processing data, a non-volatile read only memory (ROM) may be integrated on the IC with instructions for operating or booting the video processor 212. This ROM may be minimized to match a minimum size needed to provide basic functionality for gathering sensor data from camera 214, such that no extra functionality that would cause delays in boot time are present. The ROM may be configured with direct memory access (DMA) to the volatile memory of the microprocessor of video processor 212. DMA allows memory-to-memory transfer of data from the ROM to system memory of the video processor 212 independently of operation of a main controller of video processor 212. Providing DMA to this boot ROM further reduces the amount of time from power on of the video processor 212 until sensor data from the camera 214 can be processed and stored. In certain embodiments, minimal processing of the camera signal from the camera 214 is performed by the video processor 212, and additional processing may be performed by applications operating on the client device 290 or server system 298.

Low-power circuitry 220 includes low-power processor 222 and low-power wireless circuitry 224. These elements of low-power circuitry 220 may be implemented as separate elements or may be implemented on a single IC as part of a system on a single chip. Low-power processor 222 includes logic for managing the other elements of the device 210. As described above, for example, low power processor 222 may accept user input signals from an interface 216. Low-power processor 222 may also be configured to receive input signals or instruction communications from client device 290 via low-power wireless connection 225. Additional details related to such instructions are described further below. Low-power wireless circuitry 224 includes circuit elements for implementing a low-power wireless communication system. Bluetooth™ Smart, also known as Bluetooth™ low energy, is one standard implementation of a low power wireless communication system that may be used to implement low-power wireless circuitry 224. In other embodiments, other low power communication systems may be used.

High-speed circuitry 230 includes high-speed processor 232, memory 234, and high-speed wireless circuitry 236. High-speed processor 232 may be any processor capable of managing high-speed communications and operation of any general computing system needed for device 210. High speed processor 232 includes processing resources needed for managing high-speed data transfers on high-speed wireless connection 237 using high-speed wireless circuitry 236. In certain embodiments, the high-speed processor 232 executes an operating system such as a LINUX operating system or other such operating system such as operating system 904 of FIG. 9. In addition to any other responsibilities, the high-speed processor 232 executing a software architecture for the device 210 is used to manage data transfers with high-speed wireless circuitry 236. In certain embodiments, high-speed wireless circuitry 236 is configured to implement Institute of Electrical and Electronic Engineers (IEEE) 802.11 communication standards, also referred to herein as Wi-Fi. In other embodiments, other high-speed communications standards may be implemented by high-speed wireless circuitry 236.

Memory 234 includes any storage device capable of storing camera data generated by the camera 214 and video processor 212. While memory 234 is shown as integrated with high-speed circuitry 230, in other embodiments, memory 234 may be an independent standalone element of the device 210. In certain such embodiments, electrical routing lines may provide a connection through a chip that includes the high-speed processor 232 from the video processor 212 or low-power processor 222 to the memory 234. In other embodiments, the high-speed processor 232 may manage addressing of memory 234 such that the low-power processor 222 will boot the high-speed processor 232 any time that a read or write operation involving memory 234 is needed.

In various embodiments, the IMU 215 and/or the high-speed circuitry 230 may consume power as part of the operation of the camera device 210 and in the course of performing one or more functions such as measuring accelerations, detecting touch events, and other functions. The disclosed embodiments may provide for reduced power consumption of the IMU 215 and/or the high speed circuitry 230 when compared to other methods.

FIGS. 3 and 4 illustrate two embodiments of glasses which include display systems. In various different embodiments, such display systems may be integrated with the camera devices discussed above, or may be implemented as wearable devices without an integrated camera. In embodiments without a camera, power conservation systems and methods continue to operate for the display system and other such systems in a manner similar to what is described above for the video processor and data transfer elements of the camera devices.

FIG. 3 illustrates glasses 361 having an integrated display 211. The glasses 361 can be of any suitable type, including glasses 31, and like reference numerals have been used to describe like components of glasses 361 and 31. For simplicity, only a portion of the glasses 361 are shown in FIG. 3. Headwear or glasses 361 can optionally include left and right optical lenses 362, 563 secured within respective left and right optical element holders 36, 37. The glasses 361 can additionally include any suitable left and right optical elements or assemblies 366, which can be similar to any of the optical elements or assemblies discussed herein including optical elements 43, 44 of glasses 31. Although only one optical assembly 366 is shown in FIG. 3, it is appreciated that an optical assembly 366 can be provided for both eyes of the user.

In one embodiment, the optical assembly 366 includes any suitable display matrix 367. Such a display matrix 367 can be of any suitable type, such as a liquid crystal display (LCD), an organic light-emitting diode (OLED) display, or any other such display. The optical assembly 366 also includes an optical layer or layers 368, which can be include lenses, optical coatings, prisms, mirrors, waveguides, and other optical components in any combination. In the embodiment illustrated in FIG. 3, the optical layer 368 is a prism having a suitable size and configuration and including a first surface 371 for receiving light from display matrix 367 and a second surface 372 for emitting light to the eye of the user. The prism extends over all or at least a portion of the optical element holder 36, 37 so to permit the user to see the second surface 372 of the prism when the eye of the user is viewing through the corresponding optical element holder 36. The first surface 371 faces upwardly from the frame 32 and the display matrix 367 overlies the prism so that photons and light emitted by the display matrix 367 impinge the first surface 371. The prism is sized and shaped so that the light is refracted within the prism and is directed towards the eye of the user by the second surface 372. In this regard, the second surface 372 can be convex so as to direct the light towards the center of the eye. The prism can optionally be sized and shaped so as to magnify the image projected by the display matrix 367, and the light travels through the prism so that the image viewed from the second surface 372 is larger in one or more dimensions than the image emitted from the display matrix 367.

Glasses 361 can include any suitable computing system, including any of the computing devices disclosed herein, such as computer 61, 210 or machine 1000. In the embodiment of FIG. 3, computer 376 powered by a suitable rechargeable battery (not shown), which can be similar to battery 62, is provided. Computer 376 can receive a data stream from one or more image sensors 377, which may be similar to camera 69, or the camera 214, with image sensors 377 positioned such that the image sensor 377 senses the same scene as an eye of a wearer of glasses 361. Additional sensors, such as outwardly-facing geometry sensor 378, can be used for any suitable purpose, including the scanning and capturing of three-dimensional geometry that may be used by computer 376 with data from image sensors 377 to provide information via digital display matrix 367.

Computer 376 may be implemented using the processor elements of the device 210, including video processor 212, high-speed circuitry 230, and low-power circuitry 220. Computer 376 may additionally include any circuitry needed to power and process information for display matrix 367, which may be similar to display 211. In certain embodiments, video processor 212 or high-speed processor 232 may include circuitry to drive display matrix 367. In other embodiments, separate display circuitry may be integrated with the other elements of computer 376 to enable presentation of images on display matrix 367.

In various embodiments, the computer 376 may include an initial measurement unit, such as IMU 215. The disclosed embodiments may function to reduce power consumption of the computer 376 and/or the IMU 215.

FIG. 4 illustrates another example embodiment, shown as glasses 491, having another implementation of a display. Just as with glasses 361, glasses 491 can be of any suitable type, including glasses 31, and reference numerals have again been used to describe like components of glasses 491 and 361. Glasses 491 include optical lenses 492 secured within each of the left and right optical element holders 36, 37. The lens 492 has a front surface 493 and an opposite rear surface 494. The left and right end portions 41, 42 of the frame front piece 33 can include respective left and right frame extensions 496, 497 that extend rearward from the respective end portions 41, 42. Left and right temple pieces 46, 47 are provided, and can either be fixedly secured to respective frame extensions 496, 497 or removably attachable to the respective frame extensions 496, 497. In one embodiment, any suitable connector mechanism 498 is provided for securing the temple pieces 46, 47 to the respective frame extension 496, 497.

Glasses 491 includes computer 401, and just as with computer 376, computer 401 may be implemented using the processor elements of device 210, including video processor 212, high-speed circuitry 230, and low-power circuitry 220, and computer 401 may additionally include any circuitry needed to power and process information for the integrated display elements.

Sensors 402 include one or more cameras, which may be similar to camera 214 and/or other digital sensors that face outward, away from the user. The data feeds from these sensors 402 go to computer 401. In the embodiment of FIG. 4 the computer 401 is disposed within the first portion 51 of right temple piece 47, although the computer 401 could be disposed elsewhere in alternative embodiments. In the embodiment of FIG. 4, right temple piece 47 includes removable cover section 403 for access to computer 401 or other electronic components of glasses 491.

Glasses 491 include optical elements or assemblies 405, which may be similar to any other optical elements or assemblies described herein. One optical assembly 405 is shown, but in other embodiments, optical assemblies may be provided for both eyes of a user. Optical assembly 405 includes laser projector 407, which is a three-color laser projector using a scanning mirror or galvanometer. During operation, an optical source such as a laser projector is disposed in one of the arms or temples of the glasses, and is shown in right temple piece 47 of glasses 491. The computer 401 connects to the laser projector 407. The optical assembly 605 includes one or more optical strips 411. The optical strips 411 are spaced apart across the width of lens 492, as illustrated by lens 492 in right optical element holder 37 of FIG. 4. In other embodiments, the optical strips 411 may be spaced apart across a depth of the lens 492 between the front surface 493 and the rear surface 494 of lens 492 as shown in the partial view of lens 492 in the top corner of FIG. 4.

During operation, computer 401 sends data to laser projector 407. A plurality of light paths 412 are depicted, showing the paths of respective photons emitted by the laser projector 407. The path arrows illustrate how lenses or other optical elements direct the photons on paths 412 that take the photons from the laser projector 407 to the lens 492. As the photons then travel across the lens 492, the photons encounter a series of optical strips 411. When a particular photon encounters a particular optical strip 411, it is either redirected towards the user's eye, or it passes to the next optical strip 411. Specific photons or beams of light may be controlled by a combination of modulation of laser projector 407 and modulation of optical strips 411. Optical strips 411 may, in certain embodiments, be controlled through mechanical, acoustic, or electromagnetic signals initiated by computer 401.

In one example implementation of the optical strips 411, each strip 411 can use Polymer Dispersed Liquid Crystal to be opaque or transparent at a given instant of time, per software command from computer 401. In a different example implementation of the optical strips 411, each optical strip 411 can have a specific wavelength of light that it redirects toward the user, passing all the other wavelengths through to the next optical strip 411. In a different example implementation of the optical strips 411, each strip 411 can have certain regions of the strip 411 that cause redirection with other regions passing light, and the laser projector 407 can use high precision steering of the light beams to target the photons at the desired region of the particular intended optical strip 411.

In the embodiment of lens 492 illustrated in the top left of FIG. 4, optical strips 411 are disposed in and spaced apart along the width of a first layer 416 of the lens 492, which is secured in a suitable manner to a second layer 417 of the lens 492. In one embodiment, the front surface 493 is formed by the second layer 417 and the rear surface 494 is formed by the first layer 416. The second layer 417 can be provided with reflective coatings on at least a portion of the surfaces thereof so that the laser light bounces off such surfaces so as to travel along the layer 417 until the light encounters a strip 411 provided in the first layer 416, and is either redirected towards the eye of the user or continues on to the next strip 411 in the manner discussed above.

In various embodiments, the computer 401 may include an accelerometer or inertial measurement unit, such as the IMU 215 discussed above with respect to FIG. 2. The IMU and/or computer 401 may consume power as part of glasses 491 operations for capturing images, transmitting data, or performing other computing processes. Embodiments described herein may function to reduce power consumption of the computer 401 and/or IMU 215 in wearable devices such as glasses 491.

FIG. 5 is a state transition diagram that may be implemented in at least some of the disclosed embodiments. For example, in some aspects, the states illustrated in FIG. 5 may be implemented in the high speed circuitry 230 discussed above with respect to FIG. 2, and in particular to the control of the IMU 215 in some aspects. In some aspects, instructions stored in the memory 234 may configure the high speed processor 232 in some aspects to control the IMU 215.

The state transition diagram shows three states 502 a-c. State 502 a is considered a no-motion state, in that state 502 a is entered if no motion is detected by the IMU 215 for a period of time. For example, FIG. 5 shows state 502 a being entered if no motion is detected within ten (10) seconds. While in the state 502 a, a sampling rate of the IMU 215 is set to a first rate. While operating at the first rate, the IMU 215 may be unable to detect a direction of motion, but may be able to detect that motion occurred in some direction. Because the first rate is relatively low, the IMU 215 consumes a relatively low amount of power in the first state 502 a.

If motion is detected, the IMU 215 is transitioned to a second state, called the “Active” state 502 b. While in the “active” state, the IMU 215 sampling rate is set to a second rate, which is higher than the first rate. Thus, the IMU 215 may consume a greater amount of power while in the “active” state 502 b than it did when it was in the “no-motion” state 502 a, which has a lower sampling rate. While in the “active” state 502 b, the IMU 215 may be able to detect a tap event. For example, a tap event may be a tap along a side of the glasses 31, 361 or 491.

Upon detecting a tap, the IMU 215 may be transitioned from the “active” state 502 b to the state 502 c, called the “Second-Tap Detect state.” While in the state 502 c, the IMU 215 may have a third sampling rate, higher than the second sampling rate. The third state may also enable an acceleration measurement storage capability, which stores a number of acceleration measurements in a queue. Maintaining this queue requires additional power. Thus, due to the faster sampling rate and acceleration measurement queue, the third state 502 c may consume more power than the second state 502 b. Because the IMU 215 is sampling at a higher third rate, the IMU may be able to detect “double tap” events, which include two taps within a predetermined time period. If a second tap is detected while the IMU 215 is in the state 502 c, a predetermined action 520 may be taken. For example, FIG. 5 shows that a battery check LED animation may be shown. The IMU 215 may then be transitioned back to state 502 b.

If no tap is detected while in the state 502 c, within a predetermined amount of time, the IMU 215 may be transitioned back to the state 502 b.

FIG. 6 is a block diagram of an example IMU 215. The example IMU 215 of FIG. 6 includes an interface 601, a clock 602, a processor 604, a memory 606, and three motion sensors 608 a-c. The interface 601 may provide a way for the processor 604 to receive commands. For example, the interface 601 may allow the processor 604 to receive commands from the high speed processor 232 in some aspects. The interface 601 may also provide a way for the processor 604 to provide acceleration data outside the IMU 215. For example, the processor 604 may send acceleration measurements from the IMU 215 to the processor 232 via the interface 601 in some aspects. The clock 602 may synchronize the processor 604. For example, the clock 602 may signal the processor 604 at a periodic interval. The signal from the clock 602 may be utilized, in some aspects, by the processor 604 to determine a rate at which to poll the motion sensors 608 a-c, as discussed further below.

In some aspects, the memory 606 may store instructions that configure the processor 604 to perform one or more functions of the IMU 215. In some aspects, the memory 606 may store one or more acceleration measurements received from one or more of the motion sensors. For example, the memory 606 may store a queue of acceleration measurements from the motion sensors 608 a-c in some aspects.

The processor 604 may poll the three motion sensors 608 a-c at a rate. The rate may be variable, and may be set by commands received over the interface 601. For example, in some aspects, the high speed processor 232 may set a rate of that the processor 604 is to poll the three motion sensor 608 a-c. Each of the motion sensors 608 a-c may be configured to sense motion along a different axis. For example, motion sensor 608 a may be configured to sense motion along an X axis, motion sensor 608 b may be configured to sense motion along a Y axis orthogonal to the X axis, and motion sensor 608 c may be configured to sense motion along a Z axis, which is orthogonal to both the X and Y axis.

FIG. 7 is a data flow diagram of one exemplary method of training a model to detect tap inputs based on acceleration data. In some aspects, the classifier 730, discussed in more detail below, may identify one or more accelerations that represent a tap input, and one or more accelerations that do not represent a tap input. In some aspects, the classifier 730 may be utilized by block 820 and/or block 855, discussed below with respect to FIG. 8, to identify a tap input. In some aspects, one or more of the functions and/or dataflows described below with respect to dataflow 700 and FIG. 7 may be performed by the processor 232, discussed above with respect to FIG. 2. For example, instructions stored in the memory 234, may configure the processor 232 to perform one or more of the data flows and/or functions of data flow 700 discussed below.

FIG. 7 shows a training database 702. The training database 702 includes a plurality of training acceleration measurements 705. Also shown is an annotation database 706. The annotation database 706 stores annotations 708 that indicate which of the training acceleration measurements 705 indicate tap inputs and which of the training acceleration measurements 705 do not represent tap inputs.

A model builder 710 may read the acceleration measurements 705 and annotation data 708 to generate a model database 720. The model database 720 may include data representing characteristics of the tap inputs and non-tap inputs within the acceleration data 705. For example, in some aspects, the model builder 710 may apply multiple filters to the acceleration measurements 705 and generate filter outputs. The filter outputs may be stored in the model database 720 in some aspects. The model database 720 may then be utilized to determine acceleration data that represents tap inputs and acceleration data that does not represent a tap input within the acceleration measurements 705.

The classifier 730 may then read the model data 720 to determine whether acceleration data 725 corresponds to a tap event or does not correspond to a tap event. For example, in some aspects, the classifier 730 may apply various filters to the acceleration data 725, and compare filter responses to filter responses stored in the model data 1220. By identifying similarities between the filter responses from acceleration measurements annotated as tap inputs from the training data base 702, and filter responses from the acceleration data 725, the classifier 730 may generate output 740 indicating whether the acceleration data 725 is a tap input or is not a tap input.

FIG. 8 is a flowchart of a method for managing a sampling rate of an inertial measurement unit. In some aspects, one or more functions of process 800 discussed below may be performed by the IMU management application 967, discussed below with respect to FIG. 9. In some aspects, the IMU management application 967 may be running on the processor 232, discussed above with respect to FIG. 2. In some aspects, the processors 1010 discussed below with respect to FIG. 10, may be equivalent to the processor 232 discussed above with respect to FIG. 2. Furthermore, memory 1030, discussed below with respect to FIG. 10, may be equivalent to memory 234, discussed above with respect to FIG. 2. Thus, instructions 1016, discussed below with respect to FIG. 10, may configure one or more hardware processors, such as hardware processors 1010 discussed below with respect to FIG. 10, to perform one or more of the functions of process 800 discussed below. In some other embodiments, one or more of the functions of process 800 discussed below may be performed by the computer 61, the device 210, or the computers 376 and/or 401 of FIGS. 1-4 respectively.

In block 805, a device may boot. For example, in some aspects, the device may be the IMU 215. In response to the boot event of block 805, process 800 moves to block 810, where the device enters an active power state. Block 810 includes setting a sampling rate of the device to a first sampling rate. In some aspects, this rate may be high enough to provide for detection of single tap events. In some aspects, this rate may not be high enough to provide for detection of double tap events. In the active power state, the device may consume power at a first power consumption rate. The first power consumption rate may be based on the first sampling rate. As discussed above with respect to FIG. 5, the active state may not include enabling of an acceleration management queue. Thus, a history of acceleration measurements available for detection of a tap event may be limited. Block 820 determines if a tap is detected. For example, in some aspects, block 820 may analyze acceleration data received at the first sampling rate from the IMU, and determine if the acceleration data includes a tap event. In some aspects, this determination may rely on a regression model to make the determination, for example, as discussed above with respect to FIG. 7. For example, the acceleration data analyzed in block 820 may be represented by block 725 in data flow 700.

If a tap is not detected in block 820, process 800 moves to decision block 830, which determines whether a predetermined amount of time has elapsed since the device entered the active power state in block 810. If the predetermined amount of time has not elapsed, process 800 moves to wait block 835. Wait block 835 may wait a period of time indicated by the first sampling rate. For example, if decision block 820 samples the acceleration sensors 608 a-c, the amount of waiting performed by wait block 835 may determine a frequency of the sampling. After the wait is complete in block 835, processing returns to decision block 820.

If decision block 830 determines the time has elapsed, process 800 moves to block 840, where the device enters a low power state. Block 840 sets a sampling rate of the device to a second rate. The second rate is slower than the first rate set in block 810. After entering state 840 and sampling at the second rate, the device will have a second power consumption rate which is lower than the first power consumption rate the device has in the active power state of block 810. Once in the low power state of block 840, the device may be unable to detect tap inputs. Instead, the second sampling rate may support detection of motion, but may not support detection of any directional information with respect to the accelerations.

Process 800 moves from block 840 to block 845, which determines if any motion is detected. As discussed above, the lower sampling rate of block 840 may not support detection of tap events. The lower sampling rate may support detection of motion. If no motion is detected, process 800 moves from decision block 845 to wait block 847, which waits for a period of time. The wait period of block 847 may provide the second sampling rate of block 840 (the low power state). Thus, the wait period of block 847 may be longer than the wait period of block 835 in some aspects. After the wait period of block 847 completes, process returns to decision block 845. If motion is detected in block 845, process 800 moves from block 845 to block 810, where the active power state is reentered in block 810.

Returning to the discussion of decision block 820, block 820 may utilize a regression model in some aspects to determine whether a tap has been detected. For example, block 820 may analyze acceleration data, such as acceleration data 725, and determine, via classifier 730, whether a tap input has been detected based on the acceleration data. If a tap has been detected, process 800 moves from decision block 820 to block 850, which enters a third state named the “2^(nd) tap detect” state. Block 850 may increase the sampling rate of the IMU to a third rate. The third rate is faster than the first rate of block 810 and of the second rate of block 840. The third sampling rate may provide for detection of a double tap event. Block 850 may also activate an acceleration measurement storage capability in the IMU. For example, as discussed above with respect to FIG. 6, in some aspects, the IMU 215 may be configured to store acceleration measurements in the memory 606. In some aspects, any number of measurements may be stored. In some aspects, the storage may be limited based on a size of the memory 606. In some aspects, 1, 2, 3, 4, 5, 10, 15, 20, 21, 25, 30 or any number of measurements may be stored.

Process 800 moves from block 850 to decision block 855, which determines if a second tap is detected. In some aspects, decision block 855 may attempt to detect a tap event by analyzing acceleration data read from acceleration sensors (e.g. 608 a-c) via a trained classifier, such as classifier 730 discussed above. If decision block 855 detects a tap event, process 800 moves from decision block 855 to block 860, which performs an action. In some aspects, the action is to display a battery check LED animation. Other types of actions are contemplated. After the action is performed, process 800 moves from block 860 to block 810.

Returning to the discussion of decision block 855, if no tap event is detected, process 800 moves from block 855 to decision block 865, which determines if a predetermined amount of time has elapsed since entering the 2^(nd) tap detect state of block 850. In some aspects, the predetermined amount of time of block 865 is either the same or different than the predetermined amount of time of block 830. If the time has not elapsed, process 800 moves from block 865 to wait block 870. Block 870 may wait a period of time that effectively defines the third sampling rate of block 850. Thus, the waiting period of block 870 may be shorter than the waiting periods of either block 835 or block 847. After the waiting period of bock 870 is complete, process 800 moves from block 870 to decision block 855. Returning to the discussion of decision block 865, if the amount of time has elapsed, process 800 moves from decision block 865 to block 810, which reenters the active state.

While the methods described above present operations in a particular order, it will be appreciated that alternate embodiments may operate with certain operations occurring simultaneously or in a different order.

FIG. 9 is a block diagram 900 illustrating an architecture of software architecture 902, which can be installed on any one or more of the devices described above. FIG. 9 is merely a non-limiting example of a software architecture, and it will be appreciated that many other architectures can be implemented to facilitate the functionality described herein. In various embodiments, the software architecture 902 is implemented by hardware such as computer 61, device 210, computer 376, and/or computer 401 of FIGS. 1, 2, 3, and 4 respectively. In some aspects, the software 902 may be executed by a machine 1000 of FIG. 10, discussed below. The software architecture 902 may include a stack of layers where each layer may provide a particular functionality. For example, the software architecture 902 may include one or more layers such as an operating system 904, libraries 906, frameworks 908, and applications 910. Operationally, the applications 910 invoke application programming interface (API) calls 912 through the software stack and receive messages 914 in response to the API calls 912, consistent with some embodiments. In various embodiments, any client device 290, server computer of a server system 298, or any other device described herein may operate using elements of software architecture 902. Devices such as the device 210 may additionally be implemented using aspects of software architecture 902, with the architecture adapted for operating using low-power circuitry (e.g., low-power circuitry 220) and high-speed circuitry (e.g., high-speed circuitry 230) as described herein.

In various implementations, the operating system 904 manages hardware resources and provides common services. The operating system 904 includes, for example, a kernel 920, services 922, and drivers 924. The kernel 920 acts as an abstraction layer between the hardware and the other software layers consistent with some embodiments. For example, the kernel 920 provides memory management, processor management (e.g., scheduling), component management, networking, and security settings, among other functionality. The services 922 can provide other common services for the other software layers. The drivers 924 are responsible for controlling or interfacing with the underlying hardware, according to some embodiments. For instance, the drivers 924 can include display drivers, camera drivers, BLUETOOTH® or BLUETOOTH® Low Energy drivers, flash memory drivers, serial communication drivers (e.g., Universal Serial Bus (USB) drivers), WI-FI® drivers, audio drivers, power management drivers, and so forth. In certain implementations of a device such as the device 210, low-power circuitry may operate using drivers 924 that only contain BLUETOOTH® Low Energy drivers and basic logic for managing communications and controlling other devices, with other drivers operating with high-speed circuitry.

In some embodiments, the libraries 906 provide a low-level common infrastructure utilized by the applications 910. The libraries 906 can include system libraries 930 (e.g., C standard library) that can provide functions such as memory allocation functions, string manipulation functions, mathematic functions, and the like. In addition, the libraries 906 can include API libraries 932 such as media libraries (e.g., libraries to support presentation and manipulation of various media formats such as Moving Picture Experts Group-4 (MPEG4), Advanced Video Coding (H.264 or AVC), Moving Picture Experts Group Layer-3 (MP3), Advanced Audio Coding (AAC), Adaptive Multi-Rate (AMR) audio codec, Joint Photographic Experts Group (JPEG or JPG), or Portable Network Graphics (PNG)), graphics libraries (e.g., an OpenGL framework used to render in two dimensions (2D) and three dimensions (3D) in a graphic content on a display), database libraries (e.g., SQLite to provide various relational database functions), web libraries (e.g., WebKit to provide web browsing functionality), and the like. The libraries 906 can also include a wide variety of other libraries 934 to provide many other APIs to the applications 910.

The frameworks 908 provide a high-level common infrastructure that can be utilized by the applications 910, according to some embodiments. For example, the frameworks 908 provide various graphic user interface (GUI) functions, high-level resource management, high-level location services, and so forth. The frameworks 908 can provide a broad spectrum of other APIs that can be utilized by the applications 910, some of which may be specific to a particular operating system or platform.

In an example embodiment, the applications 910 may include a home application 950, a contacts application 952, a browser application 954, a location application 958, a media application 960, a messaging application 962, and a broad assortment of other applications such as a third party application 966. According to some embodiments, the applications 910 are programs that execute functions defined in the programs. Various programming languages can be employed to create one or more of the applications 910, structured in a variety of manners, such as object-oriented programming languages (e.g., Objective-C, Java, or C++) or procedural programming languages (e.g., C or assembly language). In a specific example, the third party application 966 (e.g., an application developed using the ANDROID™ or IOS™ software development kit (SDK) by an entity other than the vendor of the particular platform) may be mobile software running on a mobile operating system such as IOS™, ANDROID™, WINDOWS® Phone, or another mobile operating systems. In this example, the third party application 966 can invoke the API calls 912 provided by the operating system 904 to facilitate functionality described herein.

Embodiments described herein may particularly interact with an inertial measurement unit (IMU) management application 967. Such an application 967 may interact with motion component 1058, discussed below with respect to FIG. 10, to provide detection of touch inputs while managing power consumption, as discussed above, for example, with respect to FIGS. 5 and/or 8.

The software architecture of FIG. 9 illustrates an example architecture that may be implemented in some embodiments by a wearable device executing a mobile operating system (e.g., IOS™, ANDROID™, WINDOWS® Phone, or other mobile operating systems), consistent with some embodiments. In one embodiment, the wearable device detects touch inputs from the user via the information provided by an acceleration sensor or inertial measurement unit.

FIG. 10 shows a diagrammatic representation of a machine 1000 in the example form of a computer system, within which instructions 1016 (e.g., software, a program, an application, an applet, an app, or other executable code) for causing the machine 1000 to perform any one or more of the methodologies discussed herein can be executed. In alternative embodiments, the machine 1000 operates as a standalone device or can be coupled (e.g., networked) to other machines. In a networked deployment, the machine 1000 may operate in the capacity of a server machine or a client machine in a server-client network environment, or as a peer machine in a peer-to-peer (or distributed) network environment. The machine 1000 can comprise, but not be limited to, a server computer, a client computer, a personal computer (PC), a tablet computer, a laptop computer, a netbook, a set-top box (STB), a personal digital assistant (PDA), an entertainment media system, a cellular telephone, a smart phone, a mobile device, a wearable device (e.g., a smart watch), a smart home device (e.g., a smart appliance), other smart devices, a web appliance, a network router, a network switch, a network bridge, or any machine capable of executing the instructions 1016, sequentially or otherwise, that specify actions to be taken by the machine 1000. Further, while only a single machine 1000 is illustrated, the term “machine” shall also be taken to include a collection of machines 1000 that individually or jointly execute the instructions 1016 to perform any one or more of the methodologies discussed herein.

In various embodiments, the machine 1000 comprises processors 1010, memory 1030, and I/O components 1050, which can be configured to communicate with each other via a bus 1002. In an example embodiment, the processors 1010 (e.g., a Central Processing Unit (CPU), a Reduced Instruction Set Computing (RISC) processor, a Complex Instruction Set Computing (CISC) processor, a Graphics Processing Unit (GPU), a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Radio-Frequency Integrated Circuit (RFIC), another processor, or any suitable combination thereof) include, for example, a processor 1012 and a processor 1014 that may execute the instructions 1016. The term “processor” is intended to include multi-core processors that may comprise two or more independent processors (also referred to as “cores”) that can execute instructions contemporaneously. Although FIG. 10 shows multiple processors 1010, the machine 1000 may include a single processor with a single core, a single processor with multiple cores (e.g., a multi-core processor), multiple processors with a single core, multiple processors with multiples cores, or any combination thereof.

The memory 1030 comprises a main memory 1032, a static memory 1034, and a storage unit 1036 accessible to the processors 1010 via the bus 1002, according to some embodiments. The storage unit 1036 can include a machine-readable medium 1038 on which are stored the instructions 1016 embodying any one or more of the methodologies or functions described herein. The instructions 1016 can also reside, completely or at least partially, within the main memory 1032, within the static memory 1034, within at least one of the processors 1010 (e.g., within the processor's cache memory), or any suitable combination thereof, during execution thereof by the machine 1000. Accordingly, in various embodiments, the main memory 1032, the static memory 1034, and the processors 1010 are considered machine-readable media 1038.

As used herein, the term “memory” refers to a machine-readable medium 1038 able to store data temporarily or permanently and may be taken to include, but not be limited to, random-access memory (RAM), read-only memory (ROM), buffer memory, flash memory, and cache memory. While the machine-readable medium 1038 is shown in an example embodiment to be a single medium, the term “machine-readable medium” should be taken to include a single medium or multiple media (e.g., a centralized or distributed database, or associated caches and servers) able to store the instructions 1016. The term “machine-readable medium” shall also be taken to include any medium, or combination of multiple media, that is capable of storing instructions (e.g., instructions 1016) for execution by a machine (e.g., machine 1000), such that the instructions, when executed by one or more processors of the machine 1000 (e.g., processors 1010), cause the machine 1000 to perform any one or more of the methodologies described herein. Accordingly, a “machine-readable medium” refers to a single storage apparatus or device, as well as “cloud-based” storage systems or storage networks that include multiple storage apparatus or devices. The term “machine-readable medium” shall accordingly be taken to include, but not be limited to, one or more data repositories in the form of a solid-state memory (e.g., flash memory), an optical medium, a magnetic medium, other non-volatile memory (e.g., Erasable Programmable Read-Only Memory (EPROM)), or any suitable combination thereof. The term “machine-readable medium” specifically excludes non-statutory signals per se.

The I/O components 1050 include a wide variety of components to receive input, provide output, produce output, transmit information, exchange information, capture measurements, and so on. In general, it will be appreciated that the I/O components 1050 can include many other components that are not shown in FIG. 10. The I/O components 1050 are grouped according to functionality merely for simplifying the following discussion, and the grouping is in no way limiting. In various example embodiments, the I/O components 1050 include output components 1052 and input components 1054. The output components 1052 include visual components (e.g., a display such as a plasma display panel (PDP), a light emitting diode (LED) display, a liquid crystal display (LCD), a projector, or a cathode ray tube (CRT)), acoustic components (e.g., speakers), haptic components (e.g., a vibratory motor), other signal generators, and so forth. The input components 1054 include alphanumeric input components (e.g., a keyboard, a touch screen configured to receive alphanumeric input, a photo-optical keyboard, or other alphanumeric input components), point-based input components (e.g., a mouse, a touchpad, a trackball, a joystick, a motion sensor, or other pointing instruments), tactile input components (e.g., a physical button, a touch screen that provides location and force of touches or touch gestures, or other tactile input components), audio input components (e.g., a microphone), and the like.

In some further example embodiments, the I/O components 1050 include biometric components 1056, motion components 1058, environmental components 1060, or position components 1062, among a wide array of other components. For example, the biometric components 1056 include components to detect expressions (e.g., hand expressions, facial expressions, vocal expressions, body gestures, or eye tracking), measure biosignals (e.g., blood pressure, heart rate, body temperature, perspiration, or brain waves), identify a person (e.g., voice identification, retinal identification, facial identification, fingerprint identification, or electroencephalogram based identification), and the like. The motion components 1058 include acceleration sensor components (e.g., accelerometer), gravitation sensor components, rotation sensor components (e.g., gyroscope), and so forth. The environmental components 1060 include, for example, illumination sensor components (e.g., photometer), temperature sensor components (e.g., one or more thermometers that detect ambient temperature), humidity sensor components, pressure sensor components (e.g., barometer), acoustic sensor components (e.g., one or more microphones that detect background noise), proximity sensor components (e.g., infrared sensors that detect nearby objects), gas sensor components (e.g., machine olfaction detection sensors, gas detection sensors to detect concentrations of hazardous gases for safety or to measure pollutants in the atmosphere), or other components that may provide indications, measurements, or signals corresponding to a surrounding physical environment. The environmental components, such as the temperature sensor components that detect ambient temperature, may be utilized to manage the temperature of electronic components discussed herein.

The position components 1062 include location sensor components (e.g., a Global Positioning System (GPS) receiver component), altitude sensor components (e.g., altimeters or barometers that detect air pressure from which altitude may be derived), orientation sensor components (e.g., magnetometers), and the like.

Communication can be implemented using a wide variety of technologies. The I/O components 1050 may include communication components 1064 operable to couple the machine 1000 to a network 1080 or devices 1070 via a coupling 1082 and a coupling 1072, respectively. For example, the communication components 1064 include a network interface component or another suitable device to interface with the network 1080. In further examples, communication components 1064 include wired communication components, wireless communication components, cellular communication components, Near Field Communication (NFC) components, BLUETOOTH® components (e.g., BLUETOOTH® Low Energy), WI-FI® components, and other communication components to provide communication via other modalities. The devices 1070 may be another machine or any of a wide variety of peripheral devices (e.g., a peripheral device coupled via a Universal Serial Bus (USB)). As discussed above, in some aspects, the disclosed methods and systems may manage the transmission bandwidth of one or more of the wireless components (e.g. WiFi) and/or Bluetooth components in order to control an operating temperature of a device, such as the device 1000. In some aspects, the communication components 1064 included the low power circuitry 220 and/or high speed circuitry 230.

In some embodiments, the communication components 1064 detect identifiers or include components operable to detect identifiers. For example, the communication components 1064 include Radio Frequency Identification (RFID) tag reader components, NFC smart tag detection components, optical reader components (e.g., an optical sensor to detect a one-dimensional bar codes such as a Universal Product Code (UPC) bar code, multi-dimensional bar codes such as a Quick Response (QR) code, Aztec Code, Data Matrix, Dataglyph, MaxiCode, PDF417, Ultra Code, Uniform Commercial Code Reduced Space Symbology (UCC RSS)-2D bar codes, and other optical codes), acoustic detection components (e.g., microphones to identify tagged audio signals), or any suitable combination thereof. In addition, a variety of information can be derived via the communication components 1064, such as location via Internet Protocol (IP) geo-location, location via WI-FI® signal triangulation, location via detecting an BLUETOOTH® or NFC beacon signal that may indicate a particular location, and so forth.

Transmission Medium

In various example embodiments, one or more portions of the network 1080 can be an ad hoc network, an intranet, an extranet, a virtual private network (VPN), a local area network (LAN), a wireless LAN (WLAN), a wide area network (WAN), a wireless WAN (WWAN), a metropolitan area network (MAN), the Internet, a portion of the Internet, a portion of the Public Switched Telephone Network (PSTN), a plain old telephone service (POTS) network, a cellular telephone network, a wireless network, a WI-FI® network, another type of network, or a combination of two or more such networks. For example, the network 1080 or a portion of the network 1080 may include a wireless or cellular network, and the coupling 1082 may be a Code Division Multiple Access (CDMA) connection, a Global System for Mobile communications (GSM) connection, or another type of cellular or wireless coupling. In this example, the coupling 1082 can implement any of a variety of types of data transfer technology, such as Single Carrier Radio Transmission Technology (1×RTT), Evolution-Data Optimized (EVDO) technology, General Packet Radio Service (GPRS) technology, Enhanced Data rates for GSM Evolution (EDGE) technology, third Generation Partnership Project (3GPP) including 3G, fourth generation wireless (4G) networks, Universal Mobile Telecommunications System (UMTS), High Speed Packet Access (HSPA), Worldwide Interoperability for Microwave Access (WiMAX), Long Term Evolution (LTE) standard, others defined by various standard-setting organizations, other long range protocols, or other data transfer technology.

In example embodiments, the instructions 1016 are transmitted or received over the network 1080 using a transmission medium via a network interface device (e.g., a network interface component included in the communication components 1064) and utilizing any one of a number of well-known transfer protocols (e.g., Hypertext Transfer Protocol (HTTP)). Similarly, in other example embodiments, the instructions 1016 are transmitted or received using a transmission medium via the coupling 1072 (e.g., a peer-to-peer coupling) to the devices 1070. The term “transmission medium” shall be taken to include any intangible medium that is capable of storing, encoding, or carrying the instructions 1016 for execution by the machine 1000, and includes digital or analog communications signals or other intangible media to facilitate communication of such software.

Furthermore, the machine-readable medium 1038 is non-transitory (in other words, not having any transitory signals) in that it does not embody a propagating signal. However, labeling the machine-readable medium 1038 “non-transitory” should not be construed to mean that the medium is incapable of movement; the medium 1038 should be considered as being transportable from one physical location to another. Additionally, since the machine-readable medium 1038 is tangible, the medium 1038 may be considered to be a machine-readable device.

Language

Throughout this specification, plural instances may implement components, operations, or structures described as a single instance. Although individual operations of one or more methods are illustrated and described as separate operations, one or more of the individual operations may be performed concurrently, and nothing requires that the operations be performed in the order illustrated. Structures and functionality presented as separate components in example configurations may be implemented as a combined structure or component. Similarly, structures and functionality presented as a single component may be implemented as separate components. These and other variations, modifications, additions, and improvements fall within the scope of the subject matter herein.

Although an overview of the inventive subject matter has been described with reference to specific example embodiments, various modifications and changes may be made to these embodiments without departing from the broader scope of embodiments of the present disclosure. Such embodiments of the inventive subject matter may be referred to herein, individually or collectively, by the term “invention” merely for convenience and without intending to voluntarily limit the scope of this application to any single disclosure or inventive concept if more than one is, in fact, disclosed.

The embodiments illustrated herein are described in sufficient detail to enable those skilled in the art to practice the teachings disclosed. Other embodiments may be used and derived therefrom, such that structural and logical substitutions and changes may be made without departing from the scope of this disclosure. The Detailed Description, therefore, is not to be taken in a limiting sense, and the scope of various embodiments is defined only by the appended claims, along with the full range of equivalents to which such claims are entitled.

As used herein, the term “or” may be construed in either an inclusive or exclusive sense. Moreover, plural instances may be provided for resources, operations, or structures described herein as a single instance. Additionally, boundaries between various resources, operations, modules, engines, and data stores are somewhat arbitrary, and particular operations are illustrated in a context of specific illustrative configurations. Other allocations of functionality are envisioned and may fall within a scope of various embodiments of the present disclosure. In general, structures and functionality presented as separate resources in the example configurations may be implemented as a combined structure or resource. Similarly, structures and functionality presented as a single resource may be implemented as separate resources. These and other variations, modifications, additions, and improvements fall within a scope of embodiments of the present disclosure as represented by the appended claims. The specification and drawings are, accordingly, to be regarded in an illustrative rather than a restrictive sense.

Certain embodiments are described herein as including logic or a number of components, modules, elements, or mechanisms. Such modules can constitute either software modules (e.g., code embodied on a machine-readable medium or in a transmission signal) or hardware modules. A “hardware module” is a tangible unit capable of performing certain operations and can be configured or arranged in a certain physical manner. In various example embodiments, one or more computer systems (e.g., a standalone computer system, a client computer system, or a server computer system) or one or more hardware modules of a computer system (e.g., a processor or a group of processors) is configured by software (e.g., an application or application portion) as a hardware module that operates to perform certain operations as described herein.

In some embodiments, a hardware module is implemented mechanically, electronically, or any suitable combination thereof. For example, a hardware module can include dedicated circuitry or logic that is permanently configured to perform certain operations. For example, a hardware module can be a special-purpose processor, such as a Field-Programmable Gate Array (FPGA) or an Application Specific Integrated Circuit (ASIC). A hardware module may also include programmable logic or circuitry that is temporarily configured by software to perform certain operations. For example, a hardware module can include software encompassed within a general-purpose processor or other programmable processor. It will be appreciated that the decision to implement a hardware module mechanically, in dedicated and permanently configured circuitry, or in temporarily configured circuitry (e.g., configured by software) can be driven by cost and time considerations.

Accordingly, the phrase “hardware module” should be understood to encompass a tangible entity, be that an entity that is physically constructed, permanently configured (e.g., hardwired), or temporarily configured (e.g., programmed) to operate in a certain manner or to perform certain operations described herein. As used herein, “hardware-implemented module” refers to a hardware module. Considering embodiments in which hardware modules are temporarily configured (e.g., programmed), each of the hardware modules need not be configured or instantiated at any one instance in time. For example, where a hardware module comprises a general-purpose processor configured by software to become a special-purpose processor, the general-purpose processor may be configured as respectively different special-purpose processors (e.g., comprising different hardware modules) at different times. Software can accordingly configure a particular processor or processors, for example, to constitute a particular hardware module at one instance of time and to constitute a different hardware module at a different instance of time.

Hardware modules can provide information to, and receive information from, other hardware modules. Accordingly, the described hardware modules can be regarded as being communicatively coupled. Where multiple hardware modules exist contemporaneously, communications can be achieved through signal transmission (e.g., over appropriate circuits and buses) between or among two or more of the hardware modules. In embodiments in which multiple hardware modules are configured or instantiated at different times, communications between such hardware modules may be achieved, for example, through the storage and retrieval of information in memory structures to which the multiple hardware modules have access. For example, one hardware module performs an operation and stores the output of that operation in a memory device to which it is communicatively coupled. A further hardware module can then, at a later time, access the memory device to retrieve and process the stored output. Hardware modules can also initiate communications with input or output devices, and can operate on a resource (e.g., a collection of information).

The various operations of example methods described herein can be performed, at least partially, by one or more processors that are temporarily configured (e.g., by software) or permanently configured to perform the relevant operations. Whether temporarily or permanently configured, such processors constitute processor-implemented modules that operate to perform one or more operations or functions described herein. As used herein, “processor-implemented module” refers to a hardware module implemented using one or more processors.

Similarly, the methods described herein can be at least partially processor-implemented, with a particular processor or processors being an example of hardware. For example, at least some of the operations of a method can be performed by one or more processors or processor-implemented modules. Moreover, the one or more processors may also operate to support performance of the relevant operations in a “cloud computing” environment or as a “software as a service” (SaaS). For example, at least some of the operations may be performed by a group of computers (as examples of machines including processors), with these operations being accessible via a network (e.g., the Internet) and via one or more appropriate interfaces (e.g., an Application Program Interface (API)).

The performance of certain of the operations may be distributed among the processors, not only residing within a single machine, but deployed across a number of machines. In some example embodiments, the processors or processor-implemented modules are located in a single geographic location (e.g., within a home environment, an office environment, or a server farm). In other example embodiments, the processors or processor-implemented modules are distributed across a number of geographic locations. 

1. A method comprising: operating an inertial measurement unit (IMU) in a first state of a plurality of states, the first state having a first sampling rate of sensor data; and in response to detecting motion, transitioning the IMU to a second state of the plurality of states, the second state having a second sampling rate of the sensor data, wherein the first rate is slower than the second rate.
 2. The method of claim 1 further comprising: detecting motion in the first state without being able to determine a direction of the motion.
 3. The method of claim 1 further comprising: detecting, in the second state, directional information relating to additional motion.
 4. The method of claim 1 further comprising: detecting a first tap event while the IMU operates in the second state; and in response to detecting the first tap event, transitioning the IMU to a third state of the plurality of states, the third state storing a number of acceleration measurements.
 5. The method of claim 4 wherein the first tap event is detected by invoking a trained classifier to detect the first tap event based on acceleration data captured by the IMU.
 6. The method of claim 5, wherein invoking the trained classifier comprises comparing filter responses to the acceleration data to filter responses of training acceleration data.
 7. The method of claim 6, wherein comparing filter responses to the acceleration data to filter responses of training acceleration data comprises comparing filter responses to the acceleration data to filter responses of training acceleration data indicating a touch event and comparing the filter responses to the acceleration data to filter responses of training acceleration data that does not indicate a touch event.
 8. The method of claim 4 further comprising: detecting a third tap event while the IMU operates in the third state; and performing a predetermined action in response to detecting the third tap event.
 9. The method of claim 1 further comprising: lowering a sampling rate of the IMU in response to an absence of detecting motion for greater than a threshold duration of time.
 10. The method of claim 1 wherein the IMU consumes less power when operating in the first state than the second state.
 11. The method of claim 1 wherein the IMU is part of a wearable electronic device.
 12. The method of claim 1 wherein the IMU in the first state generates first accelerometer data at a first rate, the IMU in the second state generates second accelerometer data at a second rate, and the second rate is greater than the first rate.
 13. The method of claim 1 further comprising: setting a measurement rate of the IMU to the first sampling rate; collecting the sensor data at the first sampling rate; setting the measurement rate of the IMU to the second sampling rate; and collecting the sensor data at the second sampling rate.
 14. An electronic device comprising: memory; and one or more processors coupled to the memory, the one or more processors configured to: operating an inertial measurement unit (IMU) in a first state of a plurality of states, the first state having a first sampling rate of sensor data; and in response to detecting motion, transitioning the IMU to a second state of the plurality of states, the second state having a second sampling rate of the sensor data, wherein the first rate is slower than the second rate.
 15. The electronic device of claim 14 wherein the one or more processors are further configured to: detecting a first tap event while the IMU operates in the second state; and in response to detecting the first tap event, transitioning the IMU to a third state of the plurality of states, the third state storing a number of acceleration measurements.
 16. The electronic device of claim 15 wherein the one or more processors are further configured to: detecting a third tap event while the IMU operates in the third state; and performing a predetermined action in response to detecting the third tap event.
 17. The electronic device of claim 14 wherein the one or more processors are further configured to: detecting motion in the first state without being able to determine a direction of the motion.
 18. The electronic device of claim 14 wherein the one or more processors are further configured to: detecting, in the second state, directional information relating to additional motion.
 19. The electronic device of claim 14 wherein the one or more processors are further configured to: setting a measurement rate of the IMU to the first sampling rate; collecting the sensor data at the first sampling rate; setting the measurement rate of the IMU to the second sampling rate; and collecting the sensor data at the second sampling rate.
 20. The electronic device of claim 14 wherein the one or more processors are further configured to: lowering a sampling rate of the IMU in response to an absence of detecting motion for greater than a threshold duration of time. 